Source trustworthiness can help discerning reliable and truthful information. We offer a computable model for the dynamic assessment of sources trustworthiness based on their popularity, knowledge-ability, and reputation. We apply it to the debate among medical experts in Italy during three distinct phases of the SARS-CoV-19 pandemic, and validate it against a dataset of newspaper articles. The model shows promising results in the analysis of expert debates their impact on public opinion.

Computable Trustworthiness Ranking of Medical Experts in Italy during the SARS-CoV-19 Pandemic / D. Ceolin, F. Doneda, G. Primiero - In: GoodIT '21: Proceedings[s.l] : ACM, 2021. - ISBN 9781450384780. - pp. 271-276 (( convegno Conference on Information Technology for Social Good tenutosi a Roma nel 2021 [10.1145/3462203.3475907].

Computable Trustworthiness Ranking of Medical Experts in Italy during the SARS-CoV-19 Pandemic

G. Primiero
2021

Abstract

Source trustworthiness can help discerning reliable and truthful information. We offer a computable model for the dynamic assessment of sources trustworthiness based on their popularity, knowledge-ability, and reputation. We apply it to the debate among medical experts in Italy during three distinct phases of the SARS-CoV-19 pandemic, and validate it against a dataset of newspaper articles. The model shows promising results in the analysis of expert debates their impact on public opinion.
English
Trustworthiness; Disinformation; Trust
Settore M-FIL/02 - Logica e Filosofia della Scienza
Intervento a convegno
Esperti anonimi
Ricerca di base
Pubblicazione scientifica
   Dipartimenti di Eccellenza 2018-2022 - Dipartimento di FILOSOFIA
   MINISTERO DELL'ISTRUZIONE E DEL MERITO
GoodIT '21: Proceedings
ACM
2021
271
276
6
9781450384780
Volume a diffusione internazionale
Gold
Conference on Information Technology for Social Good
Roma
2021
crossref
Aderisco
D. Ceolin, F. Doneda, G. Primiero
Book Part (author)
open
273
Computable Trustworthiness Ranking of Medical Experts in Italy during the SARS-CoV-19 Pandemic / D. Ceolin, F. Doneda, G. Primiero - In: GoodIT '21: Proceedings[s.l] : ACM, 2021. - ISBN 9781450384780. - pp. 271-276 (( convegno Conference on Information Technology for Social Good tenutosi a Roma nel 2021 [10.1145/3462203.3475907].
info:eu-repo/semantics/bookPart
3
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/868171
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